Predictive Theoretical Model for the Selective Electroreduction of Nitrate to Ammonia

Area of Science:

• Electrochemistry
• Catalysis
• Computational Chemistry

Background:

• Electrochemical nitrate reduction (eNO3RR) offers a decentralized pathway for ammonia synthesis.
• A major challenge is the competing production of nitrite, especially at low applied potentials.
• Developing selective catalysts for ammonia over nitrite is crucial for efficient synthesis.

Purpose of the Study:

• To elucidate the reaction mechanisms governing ammonia and nitrite formation during eNO3RR.
• To identify key kinetic steps and intermediates that control selectivity.
• To develop a predictive descriptor for catalyst selectivity in eNO3RR.

Main Methods:

• Combined density functional theory (DFT) calculations and microkinetic modeling.
• Analysis of reaction pathways and energy barriers for ammonia and nitrite production.
• Experimental validation of theoretical predictions using various catalyst materials.

Main Results:

• Identified NH2OH* → NH2* as the rate-limiting step for ammonia generation at low overpotentials.
• Determined NO2* → HNO2 as the highest energy barrier step for nitrite production.
• Proposed a descriptor, ΔG1 (NH2OH* → NH2*) - ΔG2 (NO2* → HNO2), to predict the selectivity crossover potential.
• Achieved good agreement between predicted and experimental selectivity on titania at -0.66 V_RHE.

Conclusions:

• The proposed descriptor accurately predicts the ammonia/nitrite selectivity crossover potential across multiple catalysts (Ag, Cu, TiO2-, Fe3O4, Fe-MoS2, Au).
• Mechanistic insights guide the rational design of catalysts for energy-efficient and selective ammonia synthesis.
• This work provides a theoretical framework for optimizing catalysts for electrochemical nitrate reduction.